This research explores the question of how the three production factors, capital, labor, and land may impact the current level of cotton output on the Harran Plain, a major cotton production area in Turkey. The object...This research explores the question of how the three production factors, capital, labor, and land may impact the current level of cotton output on the Harran Plain, a major cotton production area in Turkey. The objective of this paper is to estimate a Translog production function and compare the results to those from a Cobb-Douglas specification. Nested tests we performed resulted in the conclusion that the constant returns to scale, weak separability and Cobb-Douglas hypotheses are all satisfied. Thus the Cobb-Douglas specification is a superior functional form yielding results more robust than those from the translog model. Dwelling on Cobb-Douglas estimation results, farm size is found the most influential variable determining cotton output, followed by the variable representing capital as the second influential. Results also demonstrate that the returns-to-scale parameter calculated for this sample is not statistically different from unity, suggesting that cotton production technology in this region exhibits constant returns to scale. This result is consistent with current literature findings that render support to an inverse relationship between farm size and productivity in developing countries.展开更多
[Objective] To analyze the input and output in rice cultivation based on CD function. [Method] Based on the input factors, Cobb-Douglas production （CD） function was used to do the quantitative analysis on the input-...[Objective] To analyze the input and output in rice cultivation based on CD function. [Method] Based on the input factors, Cobb-Douglas production （CD） function was used to do the quantitative analysis on the input-output in rice production with rice growers as the objective. [Result] Considering the substitution effect of labor in- put and capital input, under the same technical conditions, the effect of increasing labor input on the rice production in per 667 m2 was negative, based on which 2 pieces of policy suggestions were put forward to promote the transfer of surplus la- bor force of rice growers and ensure the capital supply for rice production. [Conclusion] This study laid the foundation for the realization of reasonable allocation of rice production resources.展开更多
Recently, businessmen as well as industrialists are very much concerned about the theory of firm in order to make correct decisions regarding what items, how much and how to produce them. All these decisions are direc...Recently, businessmen as well as industrialists are very much concerned about the theory of firm in order to make correct decisions regarding what items, how much and how to produce them. All these decisions are directly related with the cost considerations and market situations where the firm is to be operated. In this regard, this paper should be helpful in suggesting the most suitable functional form of production process for the major manufacturing industries in Bangladesh. This paper considers Cobb-Douglas (C-D) production function with additive error and multiplicative error term. The main purpose of this paper is to select the appropriate Cobb-Douglas production model for measuring the production process of some selected manufacturing industries in Bangladesh. We use different model selection criteria to compare the Cobb-Douglas production function with additive error term to Cobb-Douglas production function with multiplicative error term. Finally, we estimate the parameters of the production function by using optimization subroutine.展开更多
In developing counties, efficiency of economic development has been determined by the analysis of industrial production. An examination of the characteristic of industrial sector is an essential aspect of growth studi...In developing counties, efficiency of economic development has been determined by the analysis of industrial production. An examination of the characteristic of industrial sector is an essential aspect of growth studies. The growth of a country can be measured by Gross Domestic Product (GDP). GDP is substantially affected by the industrial output. Industrial gross output is mainly a function of capital and labor input. If the effect of labor and capital input to output is at a satisfactory level in an industry or in a group of industries, then industrial investment will increase. As a result, the number of industries will increase, which will directly affect GDP and also will decrease the unemployment rate. This is why, industrial input-output relationship is so important for any industry as well as for the overall industrial sector of a country. To forecast the production of a firm is necessary to identify the appropriate model. MD. M. Hossain et al. [1] have shown that Cobb-Douglas production function with additive errors was more suitable for some selected manufacturing industries in Bangladesh. The main purpose of this paper is to detect the autocorrelation problem of Cobb-Douglas production model with additive errors. The result shows that autocorrelation is presented in some manufacturing industries. Finally, this paper removes the autocorrelation problem and re-estimates the parameters of the Cobb- Douglas production function with additive errors.展开更多
Gushes of Internet public opinions may trigger unexpected incidents that significantly affectsocial security and stability, especially for ones caused by the failure of public policies. Therefore,forecasting this kind...Gushes of Internet public opinions may trigger unexpected incidents that significantly affectsocial security and stability, especially for ones caused by the failure of public policies. Therefore,forecasting this kind of Interact public opinions is of great significance. The duration could be citedas one of the most direct indicators that can reflect the severity of a specific Internet public opinioncase. Based on this background, this paper aims to find the factors that may affect the duration of Internet public opinions, and accordingly proposes a model that can accurately predict the durationbefore the release of public policies. Specifically, an index system including 8 factors by consideringfour dimensions, namely, object, environment, reality （offline）, and the network （online）, isestablished. In addition, based on the dataset containing 23 typical Internet public opinion casescaused by the failure of public policies, 9 prediction models are gained by applying the multivariatelinear regression model, multivariate nonlinear regression model, and the Cobb-Douglas function.展开更多
A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synth...A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.展开更多
This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared ...This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.展开更多
Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the m...Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.展开更多
Saikosaponins are the major pharmacologically active components in Bupleurum genus and exhibit significant application potential in multiple fields such as immune regulation and anti-tumor activity.To elucidate the bi...Saikosaponins are the major pharmacologically active components in Bupleurum genus and exhibit significant application potential in multiple fields such as immune regulation and anti-tumor activity.To elucidate the biosynthetic pathway of saikosaponins,we identified two cytochrome P450 monooxygenases,CYP716A41 and CYP716Y4,in Bupleurum chinense.These enzymes catalyze the C-28 oxidation and C-16 hydroxylation of oleanane-type triterpene skeletons,respectively.The catalytic efficiency of CYP716A41 from a southern B.chinense variety was significantly higher than that from a northern variety.Molecular docking and mutagenesis experiments revealed that amino acid residues at sites 9 and 35 may contribute to this difference in catalytic efficiency.Additionally,under cold stress,the expression levels of both CYP450 genes and the saikosaponin contents in the leaves of southern varieties were significantly higher compared to those in northern varieties.The variation in the catalytic efficiency of CYP716A41 and the differential expression of the two CYP450 genes under cold stress during winter are associated with the differences in saikosaponin biosynthesis in the leaves of southern and northern B.chinense varieties.This is consistent with the distinct medicinal usage practices observed between southern and northern China.展开更多
Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in s...Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.展开更多
Nickel-catalyzed borylation of aryl nonaflates with B2pin2 could be realized,which proceeded effectively by means of C—O bond functionalization to afford a wide variety of valuable arylboronates in moderate to excell...Nickel-catalyzed borylation of aryl nonaflates with B2pin2 could be realized,which proceeded effectively by means of C—O bond functionalization to afford a wide variety of valuable arylboronates in moderate to excellent yields with good functionality compatibility.In addition,the gram-scale synthesis and the application of the approach in the late-stage elaboration of aryl nonaflate derived from pterostilbene could also be achieved.展开更多
Let K_(j)/Q,1≤j≤ν,ν≥2 be quadratic fields with pairwise coprime discriminants Dj,and let τ_(kj)^(K_(j))(n)be the divisor function associated to Dedekind zeta function SK_(j)(s).In this paper,we consider a multid...Let K_(j)/Q,1≤j≤ν,ν≥2 be quadratic fields with pairwise coprime discriminants Dj,and let τ_(kj)^(K_(j))(n)be the divisor function associated to Dedekind zeta function SK_(j)(s).In this paper,we consider a multidimensional general divisor problem related to the τ_(kj)^(K_(j))(n)involving several number fields over square integers,by establishing the corresponding asymptotic formula.As an application,we also obtain the asymptotic formula of variance of these coefi icients.展开更多
In recent years,researchers have extensively investigated the Hankel determinant,which consists of coefficients appearing in a holomorphic function’s Taylor-Maclaurin series.Hankel matrices are widely used in Markov ...In recent years,researchers have extensively investigated the Hankel determinant,which consists of coefficients appearing in a holomorphic function’s Taylor-Maclaurin series.Hankel matrices are widely used in Markov processes,non-stationary signals,and other mathematical disciplines.The aim of the current research article is to first improve the bounds of coefficient-related problems by employing the well-known Carathéodory function.The problems that we are going to improve were obtained by Tang et al.The sharp estimates of the most difficult problem of geometric function theory known as the third-order Hankel determinant are also contributed here.Zalcman and Fekete-Szegöinequalities are also studied here for the defined family of holomorphic functions.展开更多
This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fati...This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.展开更多
Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to s...Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to symptom heterogeneity and the absence of reliable biomarkers.Artificial intelligence(AI)enables the integration of multimodal data to enhance FGID management through precision diagnostics and preventive healthcare.This minireview summarizes recent advancements in AI applications for FGIDs,highlighting progress in diagnostic accuracy,subtype classification,personalized interventions,and preventive strategies inspired by the traditional Chinese medicine concept of“treating the undiseased”.Machine learning and deep learning algorithms have demonstrated value in improving IBS diagnosis,refining FD neuro-gastrointestinal subtyping,and screening for GERD-related complications.Moreover,AI supports dietary,psychological,and integrative medicine-based interventions to improve patient adherence and quality of life.Nonetheless,key challenges remain,including data heterogeneity,limited model interpretability,and the need for robust clinical validation.Future directions emphasize interdisciplinary collaboration,the development of multimodal and explainable AI models,and the creation of patientcentered platforms to facilitate a shift from reactive treatment to proactive prevention.This review provides a systematic framework to guide the clinical application and theoretical innovation of AI in FGIDs.展开更多
Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this ...Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this issue,a robust structural damage identification method is developed,integrating a modified holistic swarm optimization(MHSO)algorithm with a hybrid objective function.The MHSO is developed by combining Hammersley sequencebased population initialization,chaotic search around the worst solution,and Hooke-Jeeves pattern search around the best solution,thereby improving both global exploration and local exploitation capabilities.A hybrid objective function is constructed by merging acceleration correlation function-based and strain correlation function-based objective functions,effectively leveraging the complementary sensitivities of global and local responses.To further suppress spurious solutions and promote sparsity in parameter estimation,an additional L0.5 regularization term is introduced.The effectiveness of the proposed method is validated through numerical simulations on a simply supported beam and a steel girder benchmark structure.Comparative studies with sequential quadratic programming,genetic algorithm,andHSO demonstrate that theMHSOachieves superior accuracy and convergence efficiency,even with limited sensors and 20%noise-contaminated measurements.Results highlight that the hybrid objective function significantly enhances the detection of both major and minor damages,while the inclusion of sparse regularization improves robustness against noise and model uncertainties.The findings indicate that the proposed framework provides a reliable and computationally efficient solution for simultaneous localization and quantification of structural damages,offering promising applicability to real-world structural health monitoring scenarios.展开更多
In molybdenum chemistry,the oxidative addition of o-quinone or 1,2-dicarbonyl compounds to molybdenum has been widely used in Mo-catalyzed C—C bond construction.The carbonyl oxidative addition to Mo(0)or Mo(Ⅱ)is the...In molybdenum chemistry,the oxidative addition of o-quinone or 1,2-dicarbonyl compounds to molybdenum has been widely used in Mo-catalyzed C—C bond construction.The carbonyl oxidative addition to Mo(0)or Mo(Ⅱ)is the critical elementary reaction of molybdenum catalysis.However,the relevant density functional theory(DFT)studies are relatively scarce,especially regarding the rational selection of functionals.In this work,14 functionals were employed to investigate the Mo-catalyzed carbonyl oxidative addition step.A benchmark study was carried out to evaluate their performance in structure optimization and energy calculation.Analyses of mean absolute error(MAE)and mean squared error(MSE)indicated that the B3LYP-D3(BJ),TPSSh,and ωB97X-D functionals exhibited superior performance in structure optimization.Using the DLPNO-CCSD(T)functional as the reference,the M06,M06-L,and MN15-L functionals exhibited good performance for energy calculation based on the structures optimized using the B3LYP-D3(BJ)functional.In particular,MN15-L provided the best performance with the smallest MAE and MSE.展开更多
文摘This research explores the question of how the three production factors, capital, labor, and land may impact the current level of cotton output on the Harran Plain, a major cotton production area in Turkey. The objective of this paper is to estimate a Translog production function and compare the results to those from a Cobb-Douglas specification. Nested tests we performed resulted in the conclusion that the constant returns to scale, weak separability and Cobb-Douglas hypotheses are all satisfied. Thus the Cobb-Douglas specification is a superior functional form yielding results more robust than those from the translog model. Dwelling on Cobb-Douglas estimation results, farm size is found the most influential variable determining cotton output, followed by the variable representing capital as the second influential. Results also demonstrate that the returns-to-scale parameter calculated for this sample is not statistically different from unity, suggesting that cotton production technology in this region exhibits constant returns to scale. This result is consistent with current literature findings that render support to an inverse relationship between farm size and productivity in developing countries.
基金Supported by the Philosophy and Social Science Foundation of Hunan Province,China(2010YBA012)~~
文摘[Objective] To analyze the input and output in rice cultivation based on CD function. [Method] Based on the input factors, Cobb-Douglas production （CD） function was used to do the quantitative analysis on the input-output in rice production with rice growers as the objective. [Result] Considering the substitution effect of labor in- put and capital input, under the same technical conditions, the effect of increasing labor input on the rice production in per 667 m2 was negative, based on which 2 pieces of policy suggestions were put forward to promote the transfer of surplus la- bor force of rice growers and ensure the capital supply for rice production. [Conclusion] This study laid the foundation for the realization of reasonable allocation of rice production resources.
文摘Recently, businessmen as well as industrialists are very much concerned about the theory of firm in order to make correct decisions regarding what items, how much and how to produce them. All these decisions are directly related with the cost considerations and market situations where the firm is to be operated. In this regard, this paper should be helpful in suggesting the most suitable functional form of production process for the major manufacturing industries in Bangladesh. This paper considers Cobb-Douglas (C-D) production function with additive error and multiplicative error term. The main purpose of this paper is to select the appropriate Cobb-Douglas production model for measuring the production process of some selected manufacturing industries in Bangladesh. We use different model selection criteria to compare the Cobb-Douglas production function with additive error term to Cobb-Douglas production function with multiplicative error term. Finally, we estimate the parameters of the production function by using optimization subroutine.
文摘In developing counties, efficiency of economic development has been determined by the analysis of industrial production. An examination of the characteristic of industrial sector is an essential aspect of growth studies. The growth of a country can be measured by Gross Domestic Product (GDP). GDP is substantially affected by the industrial output. Industrial gross output is mainly a function of capital and labor input. If the effect of labor and capital input to output is at a satisfactory level in an industry or in a group of industries, then industrial investment will increase. As a result, the number of industries will increase, which will directly affect GDP and also will decrease the unemployment rate. This is why, industrial input-output relationship is so important for any industry as well as for the overall industrial sector of a country. To forecast the production of a firm is necessary to identify the appropriate model. MD. M. Hossain et al. [1] have shown that Cobb-Douglas production function with additive errors was more suitable for some selected manufacturing industries in Bangladesh. The main purpose of this paper is to detect the autocorrelation problem of Cobb-Douglas production model with additive errors. The result shows that autocorrelation is presented in some manufacturing industries. Finally, this paper removes the autocorrelation problem and re-estimates the parameters of the Cobb- Douglas production function with additive errors.
文摘Gushes of Internet public opinions may trigger unexpected incidents that significantly affectsocial security and stability, especially for ones caused by the failure of public policies. Therefore,forecasting this kind of Interact public opinions is of great significance. The duration could be citedas one of the most direct indicators that can reflect the severity of a specific Internet public opinioncase. Based on this background, this paper aims to find the factors that may affect the duration of Internet public opinions, and accordingly proposes a model that can accurately predict the durationbefore the release of public policies. Specifically, an index system including 8 factors by consideringfour dimensions, namely, object, environment, reality （offline）, and the network （online）, isestablished. In addition, based on the dataset containing 23 typical Internet public opinion casescaused by the failure of public policies, 9 prediction models are gained by applying the multivariatelinear regression model, multivariate nonlinear regression model, and the Cobb-Douglas function.
基金supported by grants from the Guangxi Science and Technology Major Project(GKAA24206023)the Biological Breeding-National Science and Technology Major Project(2024ZD04077)+2 种基金the National Natural Science Foundation of China(32272120)the National Key Research and Development Program of China(2024YFF1000800)the Guangdong Basic Research Center of Excellence for Precise Breeding of Future Crops Major Project(FCBRCE-202502,FCBRCE-202504).
文摘A growing global population and the increasing prevalence of diet-related health issues such as“hidden hunger”,obesity,hypertension,and diabetes necessitate a fundamental rethinking of crop design and breeding.Synthetic metabolic engineering offers a method to modify and redesign metabolic pathways to increase the nutritional value of crops.We summarize recent advances in the biofortification of key nutrients including provitamin A,vitamin C,vitamin B9,iron,zinc,anthocyanins,flavonoids,and unsaturated fatty acids.We discuss the potential of multi-gene stacking,gene editing,enzyme engineering,and artificial intelligence in synthetic metabolic engineering.We propose future research directions and potential solutions centered on leveraging AI-driven systems biology,precision gene editing,enzyme engineering,agrobacterium-mediated genotype-independent transformation,and modular metabolic engineering strategies to develop next-generation nutritionally enhanced super crops and transform global food systems.
基金supported by the National Natural Science Foundation of China (No.82174074)。
文摘This study investigates the properties of high-purity starches extracted from Polygonum multiflorum(PMS)and Smilax glabra(SGS).The starches were characterized by scanning electron microscopy,Fouriertransform infrared spectroscopy,X-ray diffraction,high-performance anion-exchange chromatography,and differential scanning calorimetry.Significant differences were observed in their morphological,physicochemical,and functional properties.PMS had a smaller particle size(13.68 μm),irregular polygonal shape,A-type,lower water absorption(62.67 %),and higher oil absorption(51.17 %).In contrast,SGS exhibited larger particles(31.75 μm),a nearly spherical shape,B-type,higher crystallinity(50.66 %),and greater amylose content(21.54 %),with superior thermal stability,shear resistance,and gelatinization enthalpy.SGS also contained higher resistant starch(83.28 %) and longer average chain length(20.58 %),but showed lower solubility,swelling power,light transmittance,and freeze-thaw stability.The physicochemical properties differences in crystal pattern and particle morphology between PMS and SGS lead to distinct behaviors during in vitro digestion and fermentation.These findings highlight the potential of medicinal plant starches in functional ingredients and industrial processes.
基金Supported by the National Basic Research Program of China(2012CB025904)Zhengzhou Shengda University of Economics,Business and Management(SD-YB2025085)。
文摘Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.
基金supported by CARS(CARS-21),the CAMS Innovation Fund for Medical Sciences(2021-I2M-1-032)the Science and Technology Department of Xizang(XZ202401ZY0020)+2 种基金the Science and Technology Department of Sichuan Province(2023YFH0044,2023YFH0018)the Sichuan Province Science Foundation for Distinguished Young Scholars(2022JDJQ0006)the Doctoral Fund of Southwest University of Science and Technology(19ZX7117,21ZX7116).
文摘Saikosaponins are the major pharmacologically active components in Bupleurum genus and exhibit significant application potential in multiple fields such as immune regulation and anti-tumor activity.To elucidate the biosynthetic pathway of saikosaponins,we identified two cytochrome P450 monooxygenases,CYP716A41 and CYP716Y4,in Bupleurum chinense.These enzymes catalyze the C-28 oxidation and C-16 hydroxylation of oleanane-type triterpene skeletons,respectively.The catalytic efficiency of CYP716A41 from a southern B.chinense variety was significantly higher than that from a northern variety.Molecular docking and mutagenesis experiments revealed that amino acid residues at sites 9 and 35 may contribute to this difference in catalytic efficiency.Additionally,under cold stress,the expression levels of both CYP450 genes and the saikosaponin contents in the leaves of southern varieties were significantly higher compared to those in northern varieties.The variation in the catalytic efficiency of CYP716A41 and the differential expression of the two CYP450 genes under cold stress during winter are associated with the differences in saikosaponin biosynthesis in the leaves of southern and northern B.chinense varieties.This is consistent with the distinct medicinal usage practices observed between southern and northern China.
基金supported by the National Natural Science Foundation of China,Nos.82072165 and 82272256(both to XM)the Key Project of Xiangyang Central Hospital,No.2023YZ03(to RM)。
文摘Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.
文摘Nickel-catalyzed borylation of aryl nonaflates with B2pin2 could be realized,which proceeded effectively by means of C—O bond functionalization to afford a wide variety of valuable arylboronates in moderate to excellent yields with good functionality compatibility.In addition,the gram-scale synthesis and the application of the approach in the late-stage elaboration of aryl nonaflate derived from pterostilbene could also be achieved.
基金Supported in part by NSFC(Nos.12401011,12201214)National Key Research and Development Program of China(No.2021YFA1000700)+3 种基金Shaanxi Fundamental Science Research Project for Mathematics and Physics(No.23JSQ053)Science and Technology Program for Youth New Star of Shaanxi Province(No.2025ZC-KJXX-29)Natural Science Basic Research Program of Shaanxi Province(No.2025JC-YBQN-091)Scientific Research Foundation for Young Talents of WNU(No.2024XJ-QNRC-01)。
文摘Let K_(j)/Q,1≤j≤ν,ν≥2 be quadratic fields with pairwise coprime discriminants Dj,and let τ_(kj)^(K_(j))(n)be the divisor function associated to Dedekind zeta function SK_(j)(s).In this paper,we consider a multidimensional general divisor problem related to the τ_(kj)^(K_(j))(n)involving several number fields over square integers,by establishing the corresponding asymptotic formula.As an application,we also obtain the asymptotic formula of variance of these coefi icients.
基金supported by the NSFC(11561001)the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(NJYT18-A14)+4 种基金the NSF of Inner Mongolia(2022MS01004,2020MS01011)the Higher School Foundation of Inner Mongolia(NJZY20200)the Program for Key Laboratory Construction of Chifeng University(CFXYZD202004)the Research and Innovation Team of Complex Analysis and Nonlinear Dynamic Systems of Chifeng University(cfxykycxtd202005)the Youth Science Foundation of Chifeng University(cfxyqn202133).
文摘In recent years,researchers have extensively investigated the Hankel determinant,which consists of coefficients appearing in a holomorphic function’s Taylor-Maclaurin series.Hankel matrices are widely used in Markov processes,non-stationary signals,and other mathematical disciplines.The aim of the current research article is to first improve the bounds of coefficient-related problems by employing the well-known Carathéodory function.The problems that we are going to improve were obtained by Tang et al.The sharp estimates of the most difficult problem of geometric function theory known as the third-order Hankel determinant are also contributed here.Zalcman and Fekete-Szegöinequalities are also studied here for the defined family of holomorphic functions.
基金supported by National Natural Science Foundation of China[NO.11932013].
文摘This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.
基金Supported by The Natural Science Foundation of China,No.82374292the Plans for Major Provincial Science and Technology Projects of Anhui Province,No.202303a07020003the Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine,No.ZYYCXTD-C-202401.
文摘Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to symptom heterogeneity and the absence of reliable biomarkers.Artificial intelligence(AI)enables the integration of multimodal data to enhance FGID management through precision diagnostics and preventive healthcare.This minireview summarizes recent advancements in AI applications for FGIDs,highlighting progress in diagnostic accuracy,subtype classification,personalized interventions,and preventive strategies inspired by the traditional Chinese medicine concept of“treating the undiseased”.Machine learning and deep learning algorithms have demonstrated value in improving IBS diagnosis,refining FD neuro-gastrointestinal subtyping,and screening for GERD-related complications.Moreover,AI supports dietary,psychological,and integrative medicine-based interventions to improve patient adherence and quality of life.Nonetheless,key challenges remain,including data heterogeneity,limited model interpretability,and the need for robust clinical validation.Future directions emphasize interdisciplinary collaboration,the development of multimodal and explainable AI models,and the creation of patientcentered platforms to facilitate a shift from reactive treatment to proactive prevention.This review provides a systematic framework to guide the clinical application and theoretical innovation of AI in FGIDs.
文摘Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this issue,a robust structural damage identification method is developed,integrating a modified holistic swarm optimization(MHSO)algorithm with a hybrid objective function.The MHSO is developed by combining Hammersley sequencebased population initialization,chaotic search around the worst solution,and Hooke-Jeeves pattern search around the best solution,thereby improving both global exploration and local exploitation capabilities.A hybrid objective function is constructed by merging acceleration correlation function-based and strain correlation function-based objective functions,effectively leveraging the complementary sensitivities of global and local responses.To further suppress spurious solutions and promote sparsity in parameter estimation,an additional L0.5 regularization term is introduced.The effectiveness of the proposed method is validated through numerical simulations on a simply supported beam and a steel girder benchmark structure.Comparative studies with sequential quadratic programming,genetic algorithm,andHSO demonstrate that theMHSOachieves superior accuracy and convergence efficiency,even with limited sensors and 20%noise-contaminated measurements.Results highlight that the hybrid objective function significantly enhances the detection of both major and minor damages,while the inclusion of sparse regularization improves robustness against noise and model uncertainties.The findings indicate that the proposed framework provides a reliable and computationally efficient solution for simultaneous localization and quantification of structural damages,offering promising applicability to real-world structural health monitoring scenarios.
基金Project supported by the Fundamental Research Funds for the Central Universities(No.2042025kf0052)。
文摘In molybdenum chemistry,the oxidative addition of o-quinone or 1,2-dicarbonyl compounds to molybdenum has been widely used in Mo-catalyzed C—C bond construction.The carbonyl oxidative addition to Mo(0)or Mo(Ⅱ)is the critical elementary reaction of molybdenum catalysis.However,the relevant density functional theory(DFT)studies are relatively scarce,especially regarding the rational selection of functionals.In this work,14 functionals were employed to investigate the Mo-catalyzed carbonyl oxidative addition step.A benchmark study was carried out to evaluate their performance in structure optimization and energy calculation.Analyses of mean absolute error(MAE)and mean squared error(MSE)indicated that the B3LYP-D3(BJ),TPSSh,and ωB97X-D functionals exhibited superior performance in structure optimization.Using the DLPNO-CCSD(T)functional as the reference,the M06,M06-L,and MN15-L functionals exhibited good performance for energy calculation based on the structures optimized using the B3LYP-D3(BJ)functional.In particular,MN15-L provided the best performance with the smallest MAE and MSE.
